Skip to main content
ARS Home » Plains Area » El Reno, Oklahoma » Oklahoma and Central Plains Agricultural Research Center » Peanut and Small Grains Research Unit » Research » Publications at this Location » Publication #390193

Research Project: Management Strategies for Invasive Aphid Pests of Cereals

Location: Peanut and Small Grains Research Unit

Title: Evaluation of areawide forecasts of wind-borne crop pests: Sugarcane aphid (Hemiptera: Aphididae) infestations of sorghum in the Great Plains of North America

Author
item KORALEWSKI, TOMASZ - Texas A&M University
item WANG, HSIAO-HSUAN - Texas A&M University
item GRANT, WILLIAM - Texas A&M University
item BREWER, MICHAEL - Texas A&M University
item Elliott, Norman - Norm

Submitted to: Journal of Economic Entomology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/18/2022
Publication Date: 3/29/2022
Citation: Koralewski, T.E., Wang, H., Grant, W.E., Brewer, M.J., Elliott, N.C. 2022. Evaluation of areawide forecasts of wind-borne crop pests: Sugarcane aphid (Hemiptera: Aphididae) infestations of sorghum in the Great Plains of North America. Journal of Economic Entomology. https://doi.org/10.1093/jee/toac035.
DOI: https://doi.org/10.1093/jee/toac035

Interpretive Summary: Airborne pests pose a major challenge in agriculture. Integrated pest management programs, with their holistic approaches, have been considered a viable response to the problems. Modeling dispersal of wind-borne invasive insect pests can be a valuable tool in a broader context of areawide pest management. Airborne pests pose a major challenge in agriculture. Integrated pest management programs are considered an effective way to manage invasive insect pests. As an important component of integrated pest management programs, pest forecasting can aid in strategic management decision-making. Annually sugarcane aphid infestations of sorghum in the Great Plains of North America is a recent such challenge. A computer based mathematical model was developed that simulates sugarcane aphid infestations over the southern-to-central part of the region. In this work we evaluated model forecasts of first occurrence sugarcane aphids in fields against 2015-2018 field data on first occurrence. The ranges of days of first infestation forecasted by the model significantly overlapped with those observed in the field. The average days of first infestation observed in the field were approximated by the model with differences of less than 28 days in Texas and southern Oklahoma during 2015-2018, and in northern Oklahoma during 2016-2017. In half of these cases the difference was less than 14 days. In general, the modeled average day of first infestation was earlier than the observed one. The importance of the results is that the model appears to represent wind-borne dispersal adequately and therefore may be useful in assessing patterns of sugarcane aphid occurrence to trigger sugarcane aphid monitoring activities in fields in the Great Plains region as part of a comprehensive integrated pest management system.

Technical Abstract: Airborne pests pose a major challenge in agriculture. Integrated pest management programs, with their holistic approaches, have been considered a viable response to the problems. As an important component of such programs, pest forecasting can aid in strategic management decisions. Annually recurrent areawide sugarcane aphid [Melanaphis sacchari (Zehntner) (Hemiptera: Aphididae)] infestations of sorghum [Sorghum bicolor (L.) Moench (Poales: Poaceae)] in the Great Plains of North America is one of the more recent such challenges. As part of the response, a spatially-explicit individual-based simulation model was developed that simulates sugarcane aphid infestations over the southern-to-central part of the region. In this work we evaluated model forecasts using 2015-2018 field data. The ranges of days of first infestation forecasted by the model significantly overlapped with those observed in the field. The average days of first infestation observed in the field were approximated by the model with differences of less than 28 days in Texas and southern Oklahoma during 2015-2018, and in northern Oklahoma during 2016-2017. In half of these cases the difference was less than 14 days. In general, the modeled average day of first infestation was earlier than the observed one.